Hopf-zero bifurcation in a generalized Gopalsamy neural network model
Hopf-zero bifurcation in a generalized Gopalsamy neural network model
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DOI：
10.1007/s11071-012-0511-2
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发表时间：
2012-07
影响因子：
5.6
通讯作者：
Yuting Ding;Weihua Jiang;P. Yu
中科院分区：
文献类型：
--
作者：
Yuting Ding;Weihua Jiang;P. Yu
本文研究了一类广义Gopalsamy神经网络模型的Hopf-零分支。利用多时间尺度和中心流形约化方法，我们得到了Hopf-零临界点附近的规范形。两种方法的比较表明，这两种范式是等价的。此外，在临界点附近的二维参数空间中对分叉进行了分类，并进行了数值模拟，验证了理论结果的适用性。
In this paper, we study Hopf-zero bifurcation in a generalized Gopalsamy neural network model. By using multiple time scales and center manifold reduction methods, we obtain the normal forms near a Hopf-zero critical point. A comparison between these two methods shows that the two normal forms are equivalent. Moreover, bifurcations are classified in two-dimensional parameter space near the critical point, and numerical simulations are presented to demonstrate the applicability of the theoretical results.